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Data driven design and management of sustainability for emerging modes of supply chain


Special issue call for papers from Journal of Enterprise Information Management

Background and Motivation:

Supply chains have been understood as operational structures responsible for satisfying the customer needs at possible minimum cost. Adding the sustainability component to supply chain management (SCM) implies considering the influence and relationships between SCM and the environment as well as the social and economic aspects of the business practices (Barbosa-Póvoa, 2009). Sustainable SCM has its roots in both sustainability and SCM literatures and involves a broadened approach of supply chains. In current business environment, sustainability must integrate issues that go beyond the core concepts of the SCM such as: product design, production, distribution, end of life products and recovery processes (Lintonet al., 2007).
With the rapid development of technology, wireless transmission and sensor technology, network communication technology, cloud computing, and smart mobile devices, large amounts of data have been accumulated. Additionally, the volume of data is growing rapidly with increasingly complex structures and forms. In line with this, big data technologies such as data mining, access, processing, and statistical analysis are also getting recognition in supply chains. Applying this big data technology, supply chain members can discover, analyze and solve existing problems, and make more scientific management decisions.
Data-driven has been emerged as a new operation mode in SCM. In this sense, SCM has been greatly impacted, as supply chain members not only need to meet consumers' preferences, but also precisely match consumers' demands with manufacturers' production capacity to improve the operational efficiency. This means data-driven approach helps improve visibility throughout the supply chain, provides an integrated view of operational performance and customer interaction, and gives businesses real-time insights to make critical decisions (Choi et al. 2018). Data-driven approach has the potential to revolutionize SCM for higher competitive advanctages (Wessel and Greenberg, 2011). It was predicted early that big data analytics would revolutionize supply chain design and may influence product lifecycle management (Feng and Shanthikumar, 2018). Supply chain members need to use data-driven approach to improve the effectiveness and efficiency of decision making, produce higher-quality outputs and increase the value-added content of products and services (Lee et al., 2016; Cohen, 2018).
In recent decades, a variety of new supply chain forms and business models have been emerged, such as shared supply chain, green and or sustainable supply chain, platform supply chain, Omni-channel supply chain, crowdfunding supply chain, etc. These new business models are more closely connected with the business data. In order to improve their competitive advantages, members of these new supply chains need to make decision in the presence of huge amount of data and adjust production and operation strategies such as procurement, production, logistics, transportation, pricing, marketing, etc. in time, ultimately make their decisions sustainable. This would further assist practicing managers in improving triple bottom (economic-ecological-social) gains of supply chains (Raut et al., 2019).
In short, the design and management of sustainability in the emerging modes of the supply chains has an important issue. Therefore, this special issue aims to invite academic practitioners to contribute a better understanding of the scientific basis for this point. The scope of the research covers all aspects of sustainable development practices, assessment, and management in supply chains, and data-based analysis tools in sustainability of supply chains. Listed below are the detailed themes and objectives of this Special Issue:
1.    Theoretical and empirical analysis of different forms of sustainable development practices in data-driven supply chains. Different forms of sustainability (economic-ecological-social) are constantly emerging as social development, and the research of them is still not enough.
2.    The impact of data-driven approach on sustainability in supply chain decision-making. The traditional studies have already studied various strategies, issues, and phenomenon in the sustainability of supply chains. It is vital to verify them in the new emerging of sharing practice and compare the difference between the new one and the original one. Further, the decision-making mode of supply chain members has changed under the data-driven environment, it is necessary to establish a suitable model to investigate the impact of this change on sustainability strategies.
3.    Analytic tools in the context of big data. Data-driven approach is a useful research aspect. Especially in supply chain sustainability, appropriate data analysis tools and methods provided by researchers can help managers better investigate their customer base and provide personalized services.
4.    Performance evaluation of supply chain sustainability. The efficiency evaluation of the supply chain sustainability helps to provide scientific evaluation criteria, set benchmarks and give directions for process improvement.

Novelty of this Special Issue

There are various on-going Call-for-papers are aiming to publish articles in the domain of emerging technologies and their application in industry, and sustainability innovations for industrial and manufacturing system and SCM (Xu and Zhong, 2019; Zhong et al., 2019; Li and Huang, 2019; Mangla et al., 2018; Liu et al., 2018). In contrast with those call-for-papers, this Special Issue is focused on implementation of data driven design and management of sustainbility in emerging modes of supply chains.

Topics of interest for the Special Issue

In this special issue, we expect high-quality original research papers. This special issue encourage analytical modelers including decision making and network designs to address sustainability research in emerging modes of supply chain based on data-driven and their combination within real-life problems. Potential topics include, but are not limited to:

  •     Performance evaluation of sustainability within the data driven supply chains.
  •     Address and manage the characteristics of emerging supply chains, which is the first priority for the sustainability of supply chains.
  •     Drivers and challenges of supply chain sustainability in data-driven models.
  •    Innovations of the supply chains to increasing sustainability in data-driven environment.
  •     Technological applicability’s such as Blockchain, Industry 4.0, Big data in designing and managing sustainability in data driven supply chains.
  •     Risks and uncertainty in data-driven sustainable supply chains. Uncertainty influences the sustainable supply chains both at the supply chain structure definition as well as at the associated planning and scheduling activities.
  •     Issues related to data security, quality and management, in  data-driven models in improving supply chain sustainability.
  •     Data-driven operations management in emerging supply chains. These emerging supply chains include platform supply chain, shared supply chain, omni channel supply chain, crowd-sourcing supply chain and so on.
  •     Decision and statistical analysis in designing and managing sustainability in data driven supply chains.
  •     Cordination and collaboration in  sustainability of emerging supply chains.

 

Notes for Prospective Authors

The proposed papers should neither have been previously published nor be under active consideration for publication elsewhere. Instructions for authors can be found at the publisher’s website.

Important Dates

Contributors with proposals for papers are encouraged to communicate with the editors by e-mail. Authors should read the author guidelines found here. Papers that are currently under preparation are welcome, but we also expect papers to be written as a result of this call. The deadline for submission is December 31, 2019. Early submission is strongly recommended. The refereeing process starts once the paper is received. Accepted papers will be published online individually. The following important dates will guide the development of this SI:
•    Submission starts from: August 01, 2019. [Please select the Article Type: ‘Data-driven Supply Chain Sustainability’ in Scholar One when submitting].
•    Submission deadline: December 31, 2019.
•    Fully reviewed manuscript ready for production: August 2020.
•    Target Publication Date: December 2020.

Guest Editors

Name - Malin Song, Ph.D. (Managing Guest Editor)
Affiliation – Professor
Address - Collaborative Innovation, Center for Ecological Economics and Management, Anhui University of Finance and Economics
Telephone – +8605523171212; +8615805521822
E-mail: [email protected] ; [email protected]
My background in this area: Dr Malin Song is Professor at Anhui University of Finance and Economics (AUFE), PRC and Dean of the Collaborative Innovation Center for Ecological Economics and Management at AUFE. He was recognized as a Longhu Scholar in July 2011 and a Renowned Teacher in May 2016. In 2011 he founded the Managerial Statistics Research Center and in 2013 the Chinese Ecological Economics and Statistics Innovation Research Center at AUFE, and he has served as the Director of both since their establishment. In recent years, Professor Song has focused on research on data envelopment analysis (DEA), environmental economics, and statistics, with demonstrated achievements, especially in efficiency evaluation and applications. Since 2010, he has published more than 130 papers in international SSCI/SCI journals as the first or corresponding author, and nearly 20 papers in Chinese journals, such as Economic Research, as the first author. Professor Song is the editor-in-chief of Management of Environmental Quality and a member of the editorial boards of Energy and Environment, Journal of Chinese Management, Economic Statistics (Quarterly) and Journal of Cleaner Production. He has served as guest editor for Special Issues of Energy and Environment, Annals of Operations Research, Energy Policy, and The Journal of Cleaner Production.

Name - Sachin Kumar Mangla, Ph.D. (Co-Guest Editor)
Affilation - Lecturer in Knowledge Management and Business Decision Making, Address - Plymouth Business School, University of Plymouth, United Kingdom, PL4 8AA
Telephone - +44 (0) 1752585790
Email: [email protected][email protected]
Background in this area – Dr. Sachin K Mangla is working in the field of Green SC/Sustainability/Smart Manufacturing/Circular Economy/Risk Management/Simulation/Reverse Logistics/Energy/Decision Making and Empirical research. He loves to do research. He has published/presented several papers in repute international/national journals (RSER, TRE-D, JCP, PPC, IJPR, IJPE, ANOR, ISF, BiJ, RCR, IJLRA, IJQRM, IDMS, IJOR) and conferences (POMS, SOMS, IIIE, CILT - LRN, GLOGIFT). He has an h-index 23, i10-index 29, Google Scholar Citations of more than 1500. He is currently editing a Special issue as a Guest Editor in Production Planning & Control: The Management of Operations, and Resources, Recycling and Conservation, and Mnaagement of Envrionmental Quality, and Annals of Operations Research on 'Industry 4 and Circular Economy' and 'Operational Excellence and Sustainable Supply Chains Performance Improvement' and ‘Green Supply Chains’ and ‘Food and Drink Supply Chains’.

Name – Yang Liu, D.Sc. (Tech.). (Co-Guest Editor)
Affiliation – Associate Professor
Address - Department of Management and Engineering, Linköping University, SE-581 83 Linköping, Sweden
Telephone - +46 (0)13 28 20 54
Email: [email protected]
Background in this area – Yang Liu received his M.Sc. (Tech.) in Telecommunication Engineering and D.Sc. (Tech.) in Industrial Management from University of Vaasa, Finland, in 2005 and 2010, respectively. He is currently a tenured Associate Professor and Doctoral Supervisor in the Department of Management and Engineering at Linköping University, Sweden; a visiting faculty in the Department of Production at University of Vaasa, Finland; and a Chair Professor at Jinan University, China. Meanwhile, he is appointed Adjunct/Visiting Professor at multiple other universities. He has published over 90 peer-reviewed scientific articles. His publications have appeared in several distinguished journals, and some ranked as top 0.1% ESI Hot Papers and top 1% ESI Highly Cited Papers. He serves as an Editorial Board Member and Managing Guest Editor of the prestigious Journal of Cleaner Production (Impact Factor 2017: 5.651) as well as referee in over 30 SCI leading journals and external reviewer for NSERC of Canada. His research interests include smart manufacturing, product service innovation, decision support system, sustainable competitive advantage.

Name – Yigit Kazancoglu, Ph.D. (Co-Guest Editor)
Affiliation –Professor
Address - Department of International Logistics Management, Yasar University, Bornova, Izmir, Turkey
Telephone - +90 542 631 57 50
Email: [email protected]
Background in this area – Yigit Kazancoglu received his B.S. degree from Eastern Mediterranean University, Dept. of Industrial Engineering in 2002, and MBA from Coventry University and Izmir University of Economics, respectively in 2003 and 2004. Kazancoglu received his PhD. at Ege University (Production&Operations Management) in 2008. He was a research assistant between 2002-2005, instructor between 2005-2008, Assistant Professor Dr. between 2008-2013; and Associate Professor Dr. between Januay 2014-2016 in Izmir University of Economics, Dept. of Business Administration. Between December 2016 - May 2019 he worked as Associate Professor Dr. in Yasar University, International Logistics Management Department. In May 2019, he is assigned as Full Professor Dr. in the same department. He is the head of International Logistics Management Department in Yasar University since 2017. He has published over 40 peer-reviewed scientific articles as well as reviewer in over 25 leading journals.  His research areas are: Operations Management, Green Supply Chain Management, Circular Economy and multi criteria decision making methods.

Name - Sandun Perera, Ph.D. (Co-Guest Editor)
Affiliation - Assistant Professor of Managerial Sciences
Address - Department of Managerial Sciences, College of Business, University of Nevada, Reno, 1664 N. Virginia Street, Reno, NV 89557, USA
Telephone - +1-775-784-6993
Email: [email protected] 
Background in this area –
Sandun Perera received his Ph.D. in Operations Management as well as an MBA and an M.S. in Supply Chain Management from the University of Texas at Dallas. He also holds a Doctorate in Financial Mathematics, and Master of Science degrees in Statistics and Applied Mathematics, and in Mathematics from Florida Atlantic University. He earned his B.S. in Finance, Business and Computational Mathematics with first class honors from the University of Colombo, Sri Lanka.
His research broadly focuses on Supply Chain Management, Revenue Management, the Operations-Finance interface, the Operations-Marketing interface, Financial Engineering, and Healthcare Operations Management. His research has appeared in prestigious journals such as Production and Operations Management, Annals of Operations Research, International Journal of Production Economics, European Journal of Operational Research, Operations Research Letters, Annals of Finance and Journal of the Operational Research Society. Before joining UNR, Dr. Perera was affiliated with the Michigan Institute for Data Science (MIDAS) at the University of Michigan-Ann Arbor and the School of Management (SOM) at the University of Michigan-Flint. He has received multiple research awards and grants including the Financial Services Section Best Research Paper Award (Second Place) from the Institute for Operations Research and the Management Sciences (INFORMS) and the Outstanding Faculty Award for Research from the SOM. He currently serves on the editorial review board of the Production and Operations Management Journal and International Journal of Business Analytics.
Dr. Perera has more than 15 years of teaching experience that spans over six different universities in three different countries. He currently teaches courses on Operations and Supply Chain Management, Six-Sigma and Quality Management, Pricing, Revenue, and Predictive Analytics. He is also an active member of the Institute for Operations Research and the Management Sciences (INFORMS), the Production and Operations Management Society (POMS), Decision Sciences Institute (DSI) and the American Production and Inventory Control Society (APICS). Dr. Perera has chaired research tracks/clusters of several international conferences including the annual conference of the Decision Sciences Institute and the international meeting of the Institute for Operations Research and the Management Sciences.

References

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Choi T M, Wallace S W, Wang Y. Big data analytics in operations management. Production and Operations Management, 2018, 27(10): 1868-1883.


Cohen M C. Big data and service operations. Production and Operations Management, 2018, 27(9): 1709-1723.


Feng Q, Shanthikumar J G. How research in production and operations management may evolve in the era of big data. Production and Operations Management, 2018, 27(9): 1670-1684.


Lee B K, Zhou R, de Souza R, et al. Data-driven risk measurement of firm-to-firm relationships in a supply chain. International Journal of Production Economics, 2016, 180: 148-157.


Li Z, Huang G Q. Blockchain Technology in Industry. Call for papers for Robotics and Computer-Integrated Manufacturing, 2019, Online available at: https://www.journals.elsevier.com/robotics-and-computer-integratedmanufacturing/call-for-papers/special-issue-on-blockchain technology -in-industry


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Mangla S K, Bhattacharya A, Luthra S. Achieving Sustainability in Supply Chain Operations in the interplay between Circular Economy and Industry 4.0. Call for papers for Production Planning and Control: Management of Operations, 2018, Online available at: http://explore.tandfonline.com /cfp/est/jmt05555-tppc-achieving-sustainabilityinsupplychainoperations?utm_ source=CPB&utm_medium=cms&utm_campaign=JMT05555


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Raut R D, Mangla S K, Narwane VS, Gardas B B, Priyadarshinee P, Narkhede B E. Linking big data analytics and operational sustainability practices for sustainable business management. Journal of Cleaner Production, 2019, 224: 10-24.
Wessel D, Greenberg S. Big US firms shift hiring abroad. Wall Street Journal, 2011, 257(90): B1-B2.


Xu X, Zhong R Y. Next generation industrial and manufacturing technology. Call for papers for Computers & Industrial Engineering, 2019, Online available at: https://www.journals.elsevier.com/computers-and-industrial engineering/call-for-papers/next-generation-industrial-and-manufacturing technologies


Zhong R Y, Xu X, Battaïa O. Sustainability with Innovation for Manufacturing and Supply Chain Management. Call for papers for International Journal of Production Research, 2019, Online available at: https://think.taylorandfrancis.com/sustainability-with-innovation-for manufacturing-and supplychainmanagement/?utm_source=CPB&utm_ medium=cms&utm_campaign=JOA07875&utm_source=CPB&utm_medium=cms&utm_campaign=JMG01560